Comparing quantum-chemical calculation methods for structural investigation of zeolite crystal structures by solid-state NMR spectroscopy
Bibliographic record
Abstract
Combining quantum-chemical calculations and ultrahigh-field NMR measurements of (29)Si chemical shielding (CS) tensors has provided a powerful approach for probing the fine details of zeolite crystal structures. In previous work, the quantum-chemical calculations have been performed on 'molecular fragments' extracted from the zeolite crystal structure using Hartree-Fock methods (as implemented in Gaussian). Using recently acquired ultrahigh-field (29) Si NMR data for the pure silica zeolite ITQ-4, we report the results of calculations using recently developed quantum-chemical calculation methods for periodic crystalline solids (as implemented in CAmbridge Serial Total Energy Package (CASTEP) and compare these calculations to those calculated with Gaussian. Furthermore, in the context of NMR crystallography of zeolites, we report the completion of the NMR crystallography of the zeolite ITQ-4, which was previously solved from NMR data. We compare three options for the 'refinement' of zeolite crystal structures from 'NMR-solved' structures: (i) a simple target-distance based geometry optimization, (ii) refinement of atomic coordinates in which the differences between experimental and calculated (29)Si CS tensors are minimized, and (iii) refinement of atomic coordinates to minimize the total energy of the lattice using CASTEP quantum-chemical calculations. All three refinement approaches give structures that are in remarkably good agreement with the single-crystal X-ray diffraction structure of ITQ-4.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".